Introduction to the Modeling and Analysis of Complex Systems

16.2. SIMULATING DYNAMICS ON NETWORKS 329dynamic is taking place on a network, there is a chance for a tie (which never occurs onCA with von Neumann or Moore neighborhoods). In the example above, I just includeda tie-breaker coin toss, to be fair. And the last swap of g and nextg is something we arealready familiar with.The entire simulation code looks like this:Code 16.4: net-majority.pyimport matplotlibmatplotlib.use(’TkAgg’)from pylab import *import networkx as nxdef initialize():global g, nextgg = nx.karate_club_graph()g.pos = nx.spring_layout(g)for i in g.nodes_iter():g.node[i][’state’] = 1 if random() < .5 else 0nextg = g.copy()def observe():global g, nextgcla()nx.draw(g, cmap = cm.binary, vmin = 0, vmax = 1,node_color = [g.node[i][’state’] for i in g.nodes_iter()],pos = g.pos)def update():global g, nextgfor i in g.nodes_iter():count = g.node[i][’state’]for j in g.neighbors(i):count += g.node[j][’state’]ratio = count / (g.degree(i) + 1.0)nextg.node[i][’state’] = 1 if ratio > .5 \else 0 if ratio < .5 \else 1 if random() < .5 else 0